Welcome to the resource topic for 2014/733
Title:
Augmented Learning with Errors: The Untapped Potential of the Error Term
Authors: Rachid El~Bansarkhani, Özgür Dagdelen, Johannes Buchmann
Abstract:The Learning with Errors (LWE) problem has gained a lot of attention in recent years leading to a series of new cryptographic applications. Specifically, it states that it is hard to distinguish random linear equations disguised by some small error from truly random ones. Interestingly, cryptographic primitives based on LWE often do not exploit the full potential of the error term beside of its importance for security. To this end, we introduce a novel LWE-close assumption, namely Augmented Learning with Errors (A-LWE), which allows to hide auxiliary data injected into the error term by a technique that we call message embedding. In particular, it enables existing cryptosystems to strongly increase the message throughput per ciphertext. We show that A-LWE is for certain instantiations at least as hard as the LWE problem. This inherently leads to new cryptographic constructions providing high data load encryption and customized security properties as required, for instance, in economic environments such as stock markets resp. for financial transactions. The security of those constructions basically stems from the hardness to solve the A-LWE problem. As an application we introduce (among others) the first lattice-based replayable chosen-ciphertext secure encryption scheme from A-LWE.
ePrint: https://eprint.iacr.org/2014/733
See all topics related to this paper.
Feel free to post resources that are related to this paper below.
Example resources include: implementations, explanation materials, talks, slides, links to previous discussions on other websites.
For more information, see the rules for Resource Topics .